Data Science 101: Machine Learning, Part 5

The “How Machine Learning Works” lecture series concludes by developing some machine learning python code from scratch. We use real valued numbers sampled from two different Gaussians with different priors. Then we build an expectation maximization algorithm very similar to the previous lecture. We also show how the algorithm converges to the two clusters without any labelled training data. This lecture is presented by BloomReach engineer Srinath Sridha.

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